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Identification of neural oscillations and epileptiform changes in human brain organoids

Nature Neuroscience volume 24, pages 1488–1500 (2021)Cite this article

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Abstract

Brain organoids represent a powerful tool for studying human neurological diseases, particularly those that affect brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes, raising the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network-level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network dynamics reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from induced pluripotent stem cells from individuals with Rett syndrome, accompanied by transcriptomic differences revealed by single-cell analyses. We also rescue key physiological activities with an unconventional neuroregulatory drug, pifithrin-α. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.

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Fig. 1: Generation and characterization of fusion brain organoids.
Fig. 2: Cx + GE fusion organoids demonstrate complex neural network activities including oscillatory rhythms.
Fig. 3: Rett syndrome fused and unfused organoids have similar cortical organization and cell-type expression profiles.
Fig. 4: Single-cell transcriptomic analysis reveals the presence of diverse cellular populations in fusion organoids with a trend toward accelerated maturation and alterations in interneuron formation in MECP2-mutant samples.
Fig. 5: Gene Ontology and synaptic staining analyses reveal defects in the balance of excitatory and inhibitory synapses in MECP2-mutant fusion organoids.
Fig. 6: Rett syndrome fusion organoids display GE-dependent hypersynchronous neural network activity.
Fig. 7: Rett syndrome fusion organoids display GE-dependent epileptiform changes.
Fig. 8: Partial restoration of gamma oscillations and suppression of HFOs in Rett syndrome fusion organoids with pifithrin-α.

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Data availability

Raw and processed scRNA-seq data were deposited at the Gene Expression Omnibus under accession number GSE165577. The authors declare that all other data supporting the findings of this study are available within the paper and its Supplementary Information files.

Code availability

CNMF/CNMF-E has been previously published29,30 and the original version of CNMF_E is publicly available on GitHub at https://github.com/zhoupc/CNMF_E/. Additional code used in this study is available at https://github.com/SiFTW/CNMFeClustering/.

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Acknowledgements

We thank S. Butler, T. Carmichael and members of the laboratory of B.G.N. for helpful discussions and comments on the manuscript; N. Vishlaghi and F. Turcios-Hernandez for technical assistance, and J. Lee, S.-K. Lee, H. Shinagawa and K. Yoshikawa for valuable reagents. We also thank the UCLA Eli and Edythe Broad Stem Cell Research Center (BSCRC) and Intellectual and Developmental Disabilities Research Center microscopy cores for access to imaging facilities. This work was supported by grants from the California Institute for Regenerative Medicine (CIRM) (DISC1-08819 to B.G.N.), the National Institute of Health (R01NS089817, R01DA051897 and P50HD103557 to B.G.N.; K08NS119747 to R.A.S.; K99HD096105 to M.W.; R01MH123922, R01MH121521 and P50HD103557 to M.J.G.; R01GM099134 to K.P.; R01NS103788 to W.E.L.; R01NS088571 to J.M.P.; R01NS030549 and R01AG050474 to I.M.), and research awards from the UCLA Jonsson Comprehensive Cancer Center and BSCRC Ablon Scholars Program (to B.G.N.), the BSCRC Innovation Program (to B.G.N., K.P. and W.E.L.), the UCLA BSCRC Steffy Brain Aging Research Fund (to B.G.N. and W.E.L.) and the UCLA Clinical and Translational Science Institute (to B.G.N.), Paul Allen Family Foundation Frontiers Group (to K.P. and W.E.L.), the March of Dimes Foundation (to W.E.L.) and the Simons Foundation Autism Research Initiative Bridge to Independence Program (to R.A.S. and M.J.G.). R.A.S. was also supported by the UCLA/NINDS Translational Neuroscience Training Grant (R25NS065723), a Research and Training Fellowship from the American Epilepsy Society, a Taking Flight Award from CURE Epilepsy and a Clinician Scientist training award from the UCLA BSCRC. J.E.B. was supported by the UCLA BSCRC Rose Hills Foundation Graduate Scholarship Training Program. M.W. was supported by postdoctoral training awards provided by the UCLA BSCRC and the Uehara Memorial Foundation. O.A.M. and A.K. were supported in part by the UCLA-California State University Northridge CIRM-Bridges training program (EDUC2-08411). We also acknowledge the support of the IDDRC Cells, Circuits and Systems Analysis, Microscopy and Genetics and Genomics Cores of the Semel Institute of Neuroscience at UCLA, which are supported by the NICHD (U54HD087101 and P50HD10355701). We lastly acknowledge support from a Quantitative and Computational Biosciences Collaboratory Postdoctoral Fellowship to S.M. and the Quantitative and Computational Biosciences Collaboratory community, directed by M. Pellegrini.

Author information

Author notes

  1. Momoko Watanabe

    Present address: Department of Anatomy & Neurobiology, Sue & Bill Gross Stem Cell Research Center, School of Medicine, University of California, Irvine, Irvine, CA, USA

Authors and Affiliations

  1. Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Ranmal A. Samarasinghe, Osvaldo A. Miranda, Jessie E. Buth, Momoko Watanabe, Arinnae Kurdian, Namie N. Fotion & Bennett G. Novitch

  2. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Ranmal A. Samarasinghe, Isabella Ferando, Peyman Golshani & Istvan Mody

  3. Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA, USA

    Ranmal A. Samarasinghe, Osvaldo A. Miranda, Jessie E. Buth, Momoko Watanabe, Thomas F. Allison, Arinnae Kurdian, Namie N. Fotion, Kathrin Plath, William E. Lowry & Bennett G. Novitch

  4. Intellectual Development and Disabilities Research Center, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Ranmal A. Samarasinghe, Osvaldo A. Miranda, Jessie E. Buth, Momoko Watanabe, Arinnae Kurdian, Namie N. Fotion, Michael J. Gandal, Peyman Golshani & Bennett G. Novitch

  5. Institute for Quantitative and Computational Biosciences, Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA

    Simon Mitchell

  6. Brighton and Sussex Medical School, Falmer, United Kingdom

    Simon Mitchell

  7. Department of Biological Chemistry, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Thomas F. Allison & Kathrin Plath

  8. CIRM CSUN-UCLA Stem Cell Training Program, California State University, Northridge, CA, USA

    Arinnae Kurdian

  9. Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Michael J. Gandal

  10. Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA

    Peyman Golshani

  11. West Los Angeles VA Medical Center, Los Angeles, CA, USA

    Peyman Golshani

  12. Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA

    William E. Lowry

  13. Department of Neurology, University of Michigan Medical School, Ann Arbor, MI, USA

    Jack M. Parent

  14. Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA

    Jack M. Parent

  15. Ann Arbor VA Healthcare System, University of Michigan Medical School, Ann Arbor, MI, USA

    Jack M. Parent

  16. Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Istvan Mody

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Contributions

R.A.S., O.A.M., A.K., N.N.F. and J.M.P. performed most of the organoid culture experiments, and R.A.S. worked with other authors mentioned below on various analytical procedures. M.W., J.E.B. and B.G.N. assisted with the development of the organoid culture methods. J.E.B., T.F.A. and M.J.G. provided most of the transcriptomic analysis. B.G.N. assisted with imaging analysis. S.M. assisted R.A.S. in computational analysis of calcium indicator imaging experiments. I.F. and I.M. provided expertise in LFP recording methods and data analysis. P.G. provided guidance in two-photon calcium indicator imaging and computational methods. K.P. and W.E.L. provided the hiPSCs from individuals with Rett syndrome used in the experiments. R.A.S., J.M.P. and B.G.N. conceived, designed and supervised the experiments with helpful input from the other authors. R.A.S. and B.G.N. wrote the manuscript with editing help from the other authors.

Corresponding author

Correspondence to Bennett G. Novitch.

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Competing interests

The use of pifithrin compounds to treat Rett Syndrome and fusion organoids to screen for preclinical efficacy is covered by a patent application filed by the UC Regents with R.A.S., W.E.L. and B.G.N. as inventors. The remaining authors declare no competing interests.

Additional information

Peer review information Nature Neuroscience thanks Benjamin Philpot and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Plots and table of batch and patient line variability for key experimental measures.

a, Plots of experimental results from different batches of iCtrl and Mut Cx+GE fusion organoids analyzed for the percentage of cells in the cortical compartment that expressed tdTomato (tdTom) after the GE portion was labeled with AAV1-CAG:tdTom virus (left panel) or GAD65 antibodies (right panel). Each dot represents an individual organoid section used for analysis and numbered elements on the x-axis represent individual experiments. No within- or across-genotype differences were noted for either percentage of Cx expressing tdTom or GAD65. b,c, Plots of individual experimental results from iCtrl and Mut Cx+GE fusion calcium indicator and LFP experiments. Each dot represents results from an independent experiment, numbered elements on the x-axis represent independent organoid batches. Blue dots represent hiPSC line I (Rett patient with a 705delG frameshift mutation), green dots represent hiPSC line II (Rett patient with 1461 A > G missense mutation), and orange and red circles indicate independently isolated hiPSC lines from the same patient. For calcium indicator and LFP data, plots were generated for all experiments in which statistically significant differences between Mut and iCtrl Cx+GE fusions were reported. In all cases in which the same measure resulted in statistically significant differences between Mut and iCtrl in both hiPSC patient lines, the two patient lines were combined for within genotype statistical analyses (for example, proportion of multispiking neurons). d, Table with mean, standard deviation (Std Dev), within genotype P value, and between genotype P value for all measures shown in a-c. The results show relatively low Std Dev within genotypes as reflected in non-significant P values, yet highly significant differences between the iCtrl and Mut groups in nearly all functional measurements. All between batch statistical analyses were by ANOVA. All between genotype analyses by ANOVA with correction for multiple comparisons by Tukey’s test, unless otherwise specified in the main text.

Extended Data Fig. 2 Constrained non-negative matrix factorization (CNMF) based Ca2+ data extraction workflow and output.

a, Raw image of an GCaMP6f infected Cx+GE organoid (left) and CNMF based identification of fluorescently active (spiking) GCaMP regions of interest (right). b-d, Identification and analysis of individual neuronal Ca2+ spiking data. b, Changes in GCaMP6f fluorescence (normalized ΔF/F) for each neuron in a displayed as individual spike trains (left) or the same data displayed as a colorized amplitude plot (right). Individual spiking data are then used to determine various measures of spiking behavior including overall synchronicity based on a threshold level determined following spike shuffling c and calculation of interspike intervals d. e, Simultaneous to b-d, Ca2+ spiking data are categorized into neuronal microcircuits (clusters) based on correlations between individual Ca2+ spikes. f, during initial analyses, alternative clustering approaches including cross-correlation was used and the neural microcircuits resulting from multiple approaches were compared to determine the optimal clustering paradigm.

Extended Data Fig. 3 Immunohistochemical analyses reveal similar cell composition in iCtrl and Mut fusion organoids.

a, Day ~100 iCtrl and Mut Cx+GE fusion organoids have comparable numbers of GAD65+ positive cells in both the GE and Cx end (quantification in Fig. 3c). b, Both unfused Mut and unfused iCtrl day ~100 GE organoids contain multiple interneuron subtypes including CALRETININ, CALBINDIN, and SOMATOSTATIN (SST) expressing cells. c, Mut and iCtrl Day ~100 GE and Cx organoids also contain GFAP+ astrocytes. All images are representative examples from 3 or more independently imaged sections. See Supplementary Table 4 for additional details.

Extended Data Fig. 4 Rett syndrome fusion organoids from a second patient hiPSC line exhibit neural network irregularities in calcium indicator measurements.

a, Immunohistochemical analyses of isogenic Cx and GE organoids from a second Rett syndrome patient hiPSC line (harboring a 1461 A > G missense mutation, indicated by “II”) reveals either the presence (iCtrl-II) or absence (Mut-II) of MECP2 expression. Representative images from n = 2 independent experiments and 6 imaged sections. b, Mut-II Cx+GE fusions contain hyperexcitable neurons as indicated by the red boxed regions in the bottom ΔF/F colorized amplitude plot and spike plot. These plots show trains of repeatedly firing Ca2+ transients with short interspike intervals that are not present in iCtrl-II Cx+GE (top plots). c, There is no discernible change in synchronization of calcium transients between Mut and iCtrl as reflected in the clustergrams. d, The hyperexcitable phenotype in Mut-II Cx+GE fusions is reflected in the pooled data both by significant increases in multispiking neurons and decreases in mean and median interpeak intervals. Pooled data quantifications, n = 10 iCtrl-II and n = 6 Mut-II fusion organoids, where each n is an independently generated organoid. Two-sided Mann-Whitney tests were used, *P = 0.0071 for the proportion of multispiking neurons, **P = 0.0047 for the mean interspike interval, **P = 0.0017 for the median interspike interval, ns = not significant. Plot in d displays the full distribution of individual data points with dotted lines indicating the median and quartile values.

Extended Data Fig. 5 Enrichment of autism and epilepsy risk genes in up/downregulated genes in MECP2 mutant and isogenic control organoids.

a, Overlap of differentially expressed genes in MECP2 mutant organoids (all cell groups) with SFARI autism spectrum disorder (ASD) gene categories 1-3 and DisGeNET epilepsy Gene-Disease Association list (CUI: C0014544). Overlaps between data are indicated by red and green shading and displayed as Venn diagrams in b. c, Two-sided Fisher’s Exact Test was used to determine if Up/Downregulated genes show enrichment for genes in SFARI and epilepsy gene lists. Odds ratio from the test are displayed along with Bonferroni-corrected P values. Up/Epilepsy: ***P = 0.0016, Down/Epilepsy: ****P = 1.81×10-5, Up/ASD: ****P = 5.72×10-9, Down/ASD: P = 1.00.

Extended Data Fig. 6 UMAP representation of select genes associated with synaptogenesis and kainate responsivity.

a, UMAP representation of select genes associated with axonal projections and synaptogenesis found to be upregulated in MECP2 mutant Cx+GE fusion organoids. Violin plots display the relative expression level of each gene across the indicated cell clusters. b, UMAP representation of kainate receptor gene expression within the Cx+GE fusion organoids.

Extended Data Fig. 7 Gene ontology analysis of neuronal subtype clusters.

Top 10 most enriched Gene Ontology biological process (GO BP) terms associated with upregulated or downregulated differentially expressed genes when comparing Mut and iCtrl within the main excitatory (CPN and CFuPN) and interneuron (IN) clusters. Upregulated genes in the excitatory clusters are highly enriched for terms associated with synaptogenesis and axonal morphogenesis while downregulated genes are associated with mRNA catabolism and translation. In contrast, synaptogenesis terms are absent among the upregulated genes in the IN cluster, with this set populated by terms associated with forebrain differentiation and axonal morphogenesis. Downregulated genes in the IN cluster are enriched for metabolism and cellular cytoskeleton associated terms.

Extended Data Fig. 8 Spatially restricted microcircuit clusters and fewer synchronous events in MECP2 Mut Cx + GE organoids.

a, Pooled data for neuronal clusters derived here using Ca2+ activity correlations, reveal spatially restricted (smaller) microcircuit clusters with fewer average neurons per cluster in Mut compared to iCtrl. b, Pooled data of synchronous events demonstrates a reduced number of events, but with each event having a significantly higher amplitude (Fig. 6), in Mut compared to iCtrl. Synchronous events have similar overall duration in both conditions (n = 6 for iCtrl, n = 7 for Mut and represents independently generated organoids, *P = 0.0436 for Pairwise Distances, *P = 0.0203 for Cluster Circumference, *P = 0.0321 for Cluster Area, **P = 0.0089 for Neurons per Cluster, and *P = 0.0180 for Number of Synchronized Transients). Plots display the full distribution of individual data points with dotted lines to indicate the median and quartile values. Following a normality test, statistical significance was determined using a two-sided Mann-Whitney U-test.

Extended Data Fig. 9 Additional independent examples of local field potential recordings.

a,d, Representative raw 10-minute LFP traces (top) and time expanded segments (bottom) from either unmixed iCtrl or Mut Cx+GE fusion organoids, or Mut Cx+iCtrl GE or iCtrl Cx+Mut GE mixed fusion organoids. b,e, Morlet plots derived from the time expanded segments shown in a,d. c,f, Periodogram derived from the entire 10 min traces shown in a,d.

Extended Data Fig. 10 Rett syndrome fusion organoids from a second patient hiPSC line demonstrate epileptiform changes in extracellular recordings.

a, Raw trace of a representative 10-minute LFP recording (top) and time expanded window (bottom) from iCtrl-II, Mut-II, or Mut-II + PFT-α Cx+GE fusion organoids. b, Morlet plots showing high frequency activity associated with the time expanded segments shown in (a). (c) Periodograms derived from the entire recordings shown in a. d, Quantification of high and low gamma spectral power from LFP recordings demonstrates a significant decrease in low gamma power and a sizeable but non-significant loss of high gamma power in Mut-II Cx+GE fusions. PFT-α treatment of Mut-II Cx+GE fusions results in a statistically significant rescue of both low and high gamma oscillatory power. Low gamma; Ordinary ANOVA, overall P = 0.0024, Tukey’s Multiple comparisons, *P = 0.0313 iCtrl II vs Mut II, *P = 0.0211 Mut II vs Mut II + PFT. High gamma; Ordinary ANOVA, overall P = 0.0091, Tukey’s multiple comparisons, *P = 0.0243 Mut II vs Mut II + PFT, P = 0.09 between iCtrl-II and Mut. e, Spike frequency across multiple independent experiments Kruskal-Wallis test, overall P = 0.0003, Dunn’s multiple comparisons **P = 0.0028, *P = 0.0276. For d and e, n = 5 for iCtrl-II and Mut-II + PFT-α, n = 6 for Mut-II (total n = 16). f, Plots of high and low gamma spectral power versus spike frequency demonstrates an inverse relationship between gamma power and spiking. The solid black line is the best fit following linear regression, and the dashed magenta lines indicate 95% confidence intervals for the estimated line of best fit. The slope of the line of best fit is indicated above each graph. Plots in d and e display the full distribution of individual data points with dotted lines to indicate the median and quartile values.

Supplementary information

Supplementary Information

Supplementary Figs. 1–5 and Supplementary Table 4

Reporting Summary

Supplementary Tables 1–3

Supplementary Video 1

Live two-photon microscopic imaging of neural activities within a representative Cx + GE fusion organoid. D90 H9 hESC-derived Cx + GE fusion organoids were infected with AAV1-GCaMP6f and imaged 12 d later (D102) using two-photon confocal microscopy.

Supplementary Video 2

CNMF-E-based evaluation of calcium activities within a Cx + GE fusion organoid. The video demonstrates real-time translation of changes in GCaMP6f fluorescence shown in Supplementary Video 1 into peaks of activity used in subsequent analyses. Neurons demonstrating activity are identified and numbered on the left and normalized ΔF/F values for each neuron are plotted on the right.

Supplementary Video 3

Post hoc clustering of calcium activity. An example demonstrating the segregation of neurons based on calcium activity into microcircuit clusters. The clusters in this example are based on correlated calcium transients between individual neurons. The rows of neurons on the right represent most neurons in each cluster and are color coded. Each cluster’s calcium activity (color matched to the right) is plotted as ΔF/F values on the left. This example is from the same H9 hESC-derived Cx + GE fusion organoid shown in Supplementary Videos 1 and 2.

Supplementary Video 4

Activity profile of a representative Cx + GE fusion organoid before exposure to BMI. This video displays the baseline GCaMP6f activity profile of a D99 H9 hESC-derived Cx + GE fusion organoid immediately before addition of 100 μM of the GABAA receptor antagonist BMI.

Supplementary Video 5

Calcium transient synchrony after BMI administration to a representative Cx + GE fusion organoid. This video displays changes in the neural network activities of the Cx + GE fusion organoid shown in Supplementary Video 4 approximately 1 min after the addition of 100 μM BMI. Note the repeated synchronization of calcium transients across the organoid.

Supplementary Video 6

Neural network activity of a representative Cx + GE fusion organoid immediately before the addition of gabazine. This video displays the baseline calcium transients present in a D98 H9 hESC-derived Cx + GE fusion organoid immediately before addition of 25 μM of the GABAA receptor antagonist gabazine.

Supplementary Video 7

Neural network activity of a representative Cx + GE fusion organoid immediately after the addition of gabazine. This video displays the prominent synchronization of neuronal activities seen in the D98 Cx + GE fusion organoid shown in Supplementary Video 6 approximately 1 min after addition of 25 μM gabazine.

Supplementary Video 8

Calcium activity in an iCtrl Cx + GE fusion organoid. A representative example of live two-photon confocal imaging of GCaMP6f fluorescence from a D103 iCtrl hiPSC-derived Cx + GE fusion organoid.

Supplementary Video 9

Spontaneous synchronizations of calcium transients in an MECP2-mutant Cx + GE fusion organoid. A representative example of the abnormal synchronizations of calcium transients seen in D103 Mut hiPSC-derived Cx + GE fusion organoids.

Supplementary Video 10

Calcium activity in an iCtrl Cx + GE fusion organoid created from hiPSCs from the second individual with Rett syndrome. A representative example of live two-photon confocal imaging of GCaMP6f fluorescence within a D100 iCtrl hiPSC-derived Cx + GE fusion organoid generated from hiPSCs derived from a second individual with Rett syndrome.

Supplementary Video 11

Hyperexcitable calcium indicator activity in an MECP2-mutant Cx + GE fusion organoid created from hiPSCs from the second individual with Rett syndrome. A representative example of hyperexcitable calcium indicator activity seen in D103 Mut hiPSC-derived Cx + GE fusion organoids. The yellow arrows indicate examples of hyperexcitable neurons resulting in reduced inter-peak intervals between activations. This is representative of the calcium indicator activity seen in Mut Cx + GE organoids generated from hiPSCs from the second individual with Rett syndrome.

Supplementary Video 12

Calcium activity in a mixed Mut Cx and iCtrl GE (Mut Cx + iCtrl GE) fusion organoid. A representative example of live two-photon confocal imaging of GCaMP6f fluorescence from a D101 mixed Mut Cx + iCtrl GE hiPSC-derived fusion organoid.

Supplementary Video 13

Spontaneous synchronizations of calcium transients in a mixed iCtrl Cx and MECP2-mutant GE (iCtrl Cx + Mut GE) fusion organoid. A representative example of the abnormal synchronizations of calcium transients seen in ~D100 mixed iCtrl Cx + Mut GE hiPSC-derived fusion organoids. This example is from a D102 fusion organoid.

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Samarasinghe, R.A., Miranda, O.A., Buth, J.E. et al. Identification of neural oscillations and epileptiform changes in human brain organoids. Nat Neurosci 24, 1488–1500 (2021). https://doi.org/10.1038/s41593-021-00906-5

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